Electric utility companies regularly collect usage data from meters. Over the last few decades, many public utilities have modernized their data collection using automated meter reading (AMR) to reduce the time and expense of collecting this data manually. More recently, technology has evolved to more advanced metering systems, generally referred to as Advanced Meter Infrastructure (AMI) that allows reliable two-way communications with meters and utilities have responded to the dynamic pricing of electricity by shifting from once-a-month meter readings to daily, hourly or even sub-hourly meter readings.
To facilitate the management of the fantastic amounts of data generated from increased read frequency, many utilities are now using meter data management systems (MDMSs), which not only manage and organize the incoming AMI data into a database, but also validate it, fill in missing data, and generally ensure that utilities have sufficiently accurate data to bill their customers. One of the leading providers of MDMSs is Ecologic Analytics of Bloomington, Minn., the employer of the present inventors.
One problem recognized by the present inventors concerns AMI systems and outage management systems (OMSs). An OMS is a computer system used by utility operators to manage the restoration of electrical service in the event of a power outage. These systems typically receive telephone outage reports from customers through a call center and/or Interactive Voice Response (IVR) system, and plot them on a digital map or model of the electrical distribution network. The OMS also includes a rules engine that uses reported outage locations and the network model to determine the source and scope of the outage, and thus provide valuable information for restoring electric power to outage areas.
Although it has been known for some time that AMI systems held the potential to provide outage reports, in the form of “last gasp” messages from meters that had lost power, little if anything at all, has been achieved in actually taking advantage of this possibility. One problem is that AMI systems can generate orders of magnitude more call-equivalent “last gasp” and restore messages in any given time span time than customers can, and OMSs simply lack the capacity to handle this level of input.
Consider for example that AMI meters can report outages at any time of day or night, whereas customers may have long periods of time, such as while away at work or while sleeping, when they are unaware of power outages and thus unlikely to report them. Moreover, even when they are aware, many customers rely on their neighbors to report outages or they simply assume that the utility will already know. In contrast, all the AMI meters affected by an outage would attempt to automatically report the outage almost simultaneously regardless of time of day. Thus, larger outages affecting thousands and or even millions of customers would easily overwhelm a conventional OMS.
Another issue is that larger utilities often have a diverse set of AMI meters and Head End systems from different manufacturers, with those from one manufacturer communicating using proprietary protocols that are distinct from and incompatible with those of another. Conventional OMSs, which rely on phoned-in reports, not only lack a way of communicating with AMIs, but also have no mechanism for optimizing interactions with multiple types of AMI technologies.
Accordingly, the present inventors have recognized a need for bridging the gap between the rich data available in AMIs and the ability of OMSs to actually use it.